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                    <forename type="first">Grégory</forename>
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                <term xml:lang="en">speed profile</term>
                <term xml:lang="en">fixed-speed approximation</term>
                <term xml:lang="en">Mathematical Programming</term>
                <term xml:lang="en">optimization</term>
                <term xml:lang="en">Traffic Management</term>
                <term xml:lang="en">Traffic Management speed profile fixed-speed approximation Mathematical Programming optimization</term>
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              <p>The real-time Railway Traffic Management Problem is the problem of selecting train routes and schedules to minimize delay propagation in case of perturbation. A frequent approximation used to solve it is named fixed-speed, where the effects of accelerations and decelerations resulting from train rerouting or rescheduling are neglected. In this paper, we assess for the first time the ability of this approximation to drive the search of optimization algorithms on large infrastructures with numerous trains. This is done through a statistical analysis on a number of perturbed scenarios on different railway control areas, for various objective functions commonly used in the literature. For each scenario, we compare the ranking of hundreds of solutions, assessed, on the one hand, with the fixed-speed approximation and, on the other hand, through the variable-speed dynamics obtained through simulation. Our results indicate that the fixedspeed approximation is able to capture the relative solution quality with all considered objective functions, although some differences exist. This justifies the use of the fixed-speed approximation in optimization algorithms, to obtain practically reliable results and exploit its higher efficiency compared to more sophisticated approximations methods. We also assess a modified fixed-speed approximation that better reflects the behavior of train speed dynamics, but no remarkable difference is observable as for the quality of the approximation.</p>
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